Computational syndrome detector

ABSTRACT

Example methods disclosed herein to monitor wireless system operation include processing a plurality of session records describing characteristics of wireless sessions in a coverage area of a wireless system to determine a first time interval for a first wireless device to propagate from a first access point in the coverage area to a second access point in the coverage area, determining a coverage area traversal rate for the first wireless device based on the first time interval, the coverage area traversal rate corresponding to a rate at which the first wireless device is traversing the coverage area, and providing a wireless service advisory for the coverage area to a second wireless device based on the coverage area traversal rate for the first wireless device.

RELATED APPLICATION(S)

This patent arises from a continuation of U.S. patent application Ser.No. 11/969,131, entitled “Computational Syndrome Detector” and filed onJan. 3, 2008, which is hereby incorporated by reference in its entirety.

BACKGROUND

Devices that use wireless signaling are ubiquitous to contemporary life.Non-limiting examples of such devices include cellular telephones, textmessaging units, personal digital assistants (PDAs), and laptop andpalmtop computers. Respective such devices typically include one or moremodes of operation such as, for example, unidirectional or bidirectionalvoice, video and/or data communications, Internet accessibility, remotecontrol functionality, etc.

However, such devices are dependent upon access to wireless resources(i.e., networks or infrastructure) external to the device in order forcorresponding wireless functions to operate. For example, a cellulartelephone requires a period of continuous signal access to a cellularnetwork in order to initiate and maintain a call. Such externalresources are, as a matter of practicality, finite in their geographiccoverage range and scope of operational modes. In short, worldwidecoverage for all wireless devices, everywhere that a user might want orneed signal access, is not a reality.

Various factors result in poor or failed wireless signal access in areasthat are otherwise seemingly adequately provisioned. In one example, auser is denied wireless access while stuck in traffic because ofunusually high wireless system usage. In another example, a usertemporarily loses wireless signal access while traveling behind a largestructure in a downtown area, resulting in a “dropped” cellular phonecall. These and other scenarios cause frustration and loss ofproductivity for users of wireless technology.

SUMMARY

This summary is provided to introduce general concepts of wirelesssignal analysis and reporting methods and systems, which are furtherdescribed below in the Detailed Description. This summary is notintended to identify essential features of the claimed subject matter,nor is it intended to limit the scope of the claimed subject matter.

In one aspect, a method is performed at least in part by a computer. Themethod includes analyzing a plurality of wireless signal session datarecords. The method also includes detecting a predefined relationship inaccordance with the analysis, wherein the relationship involves one ormore wireless signal performance metrics within a geographical area. Themethod further includes generating a report in accordance with thedetecting.

In another aspect, at least one computer-readable storage media includesa program code. The program code is configured to cause one or moreprocessors to analyze a plurality of wireless signal session datarecords. The program code is also configured to cause the one or moreprocessors to detect a selectively definable pattern in accordance withthe analysis. The pattern involves one or more wireless signalperformance metrics within a geographical area. The program code isfurther configured to cause the one or more processors generate a reportin accordance with the detecting.

In yet another aspect, at least one computer-readable storage mediaincludes a program code. The program code is configured to cause one ormore processors of a wireless system to analyze a plurality of wirelesssignal session data records corresponding to two or more distinctwireless service users. The program code is also configured to cause theone or more processors to detect a selectively definable pattern inaccordance with the analysis. The pattern involves at least one wirelesssignal performance metric within a geographical area. The program codeis further configured to cause the one or more processors to generate areport in accordance with the detecting, wherein the report isconfigured to be accessed by one or more resources of the wirelesssystem.

BRIEF DESCRIPTION OF THE DRAWINGS

The detailed description is set forth with reference to the accompanyingfigures. The use of the same reference numbers in different figuresindicates similar or identical items.

FIG. 1 is a diagrammatic view depicting an illustrative operatingscenario.

FIG. 2 is a plan diagrammatic view depicting another illustrativeoperating scenario.

FIG. 3 is a flow diagram depicting a method in accordance with oneembodiment.

FIG. 4 is a flow diagram depicting a method in accordance with anotherembodiment.

FIG. 5 is a listing depicting illustrative predefined relationships inaccordance with yet another embodiment.

DETAILED DESCRIPTION

Overview:

This disclosure is directed to providing analysis and detection ofrelationships and patterns within a plurality of wireless signal sessiondata records. The analytical methods provided herein are also referredto as Syndrome Detection because the detected patterns and relationshipsare typically, but not necessarily, indicative of correspondingreal-world circumstances (syndromes). Non-limiting examples of suchrelationship/syndrome correlations include non-propagating cellularphone traffic due to an automobile collision, sudden full-capacityloading of a wireless Internet access hub due to the arrival of aninternational flight at an airport, and so on.

Illustrative Operating Scenarios:

FIG. 1 is a diagrammatic view depicting an illustrative operatingscenario 100. In FIG. 1, a wireless device 102 is present and ispresumed to be operated by a corresponding user (not shown). Forpurposes of ongoing example, it is assumed that the wireless device 102is a cellular telephone. Other wireless devices 102 (e.g., laptopcomputers, PDAs, etc.) corresponding to other, similar operationalscenarios are also contemplated within the scope of the presentteachings. The wireless device 102 is portable in nature and isconfigured to operate in one or more modes as the user moves aboutwithin a wireless signal coverage area.

The scenario 100 also includes four cellular service towers 104, 106,108 and 110, respectively. Each of the cellular towers 104, 106, 108,110 includes an area of cellular (i.e., wireless) signal coverage 114,116, 118 and 120, respectively. It is further noted that some of thecoverage areas (e.g., 114 and 116; 116 and 118) exhibit some degree ofoverlap with each other. While the respective signal coverage areas 114,116, 118, 120 are represented in FIG. 1 as hexagonal in shape, one ofordinary skill in the related arts will appreciate that suchrepresentation is a simplification for ease of understanding. In anycase, each cellular service tower 104, 106, 108, 110 can provide signalcoverage to a finite region about the respective tower. The cellularservice tower 110 further includes a finite range of Wi-Fi® signalservice as represented by coverage lobes 122. Wi-Fi® is a registeredtrademark owned by Wireless Ethernet Compatibility Alliance, Inc.,Austin, Tex., USA.

The cellular towers 104, 106, 108, 110 are coupled to a wireless system(i.e., infrastructure) 124 (such coupling is not depicted in FIG. 1).The wireless system 124 includes a database 126, a server 128 andcomputer-readable storage media 130. Non-limiting examples ofcomputer-readable storage media 130 include one or more optical disks,one or more magnetic storage media, one or more solid state memorydevices, etc. The wireless system 124 can include any other resources(not shown) as needed to support one or more wireless services (e.g.,cellular telephone, Internet access, etc.) for wireless devices (e.g.,102). Non-limiting examples of such wireless system 124 resourcesinclude additional databases, additional servers and/or computersystems, wireless signal analysis instrumentation, network and/orInternet access bridges, public switched telephone network (PSTN)interface equipment, wireless signal receivers, transmitters and/ortransceivers, etc.

In one illustrative operation, a user of the wireless device 102traverses a path 132. In doing so, the user leaves the signal coveragearea 114 at point 134 (represented by a triangle) and eventually entersthe signal coverage area 116 at a point 136 (represented by a circle).The user continues to move along the path 132 and leaves the signalcoverage area 116 at a point 138 and later enters the signal coveragearea 118 at a point 140. Thus, the user experiences a loss of wirelesssignal (e.g., cellular) access between the points 134, 136 and betweenthe points 138, 140. One or more wireless operations are not possiblealong the path 132 between the points 134, 136 and the points 138, 140,giving rise to two “blackout periods” in the context of thisillustration. Such blackout periods are a primary cause of frustrationand inefficiency for users of wireless devices.

FIG. 2 is a diagrammatic view depicting another illustrative operatingscenario 200. In FIG. 2, a divided highway 202 carries bidirectionalautomobile traffic. First and second cellular service towers 204 and206, respectively, are located within wireless service range of thehighway 202. Automobiles 208 traverse the highway 202 in a firstdirection 210.

As also depicted, automobiles 212 are at a stop along highway 202 due toa blocking collision 214. Thus, automobiles 212 are not able to proceedin their designated direction 216. Any wireless devices (not shown)within the automobiles 212 are within service range (i.e., coveragearea) of the second cellular tower 206, and are not within service rangeof the first cellular tower 204. In this way, any active such wirelessdevices (e.g., cellular telephones) within the automobiles 212 are in“stasis”, continuously accessing cellular services by way of the secondcellular tower 206. These same wireless devices are not propagating tothe first cellular tower 204 as would be the case during normal trafficflow.

Heavy cellular call traffic is therefore occurring by way of the secondcellular tower 206. In the scenario 200, such call traffic accumulatesin accordance with the growing number of stopped automobiles 212, givingrise to access saturation on the cellular tower 206. The cellular tower206 becomes loaded to capacity, and additional cellular calls (i.e.,wireless signal services) cannot be handled within the correspondingcoverage area. Detection of situations (i.e., syndromes) similar to thescenario 200 can be advantageously leveraged by commercial wirelessservice providers and the users that access their systems.

Illustrative Data Acquisition:

FIG. 3 is a flow diagram depicting a method 300 in accordance with oneembodiment. The method 300 includes particular method steps and aparticular order of execution. However, other embodiments can also beused that deviate in one or more respects from the method 300 withoutdeparting from the scope of the present teachings. For purposes ofunderstanding, certain aspects of the method 300 will be described withreference to the operational scenario 100 of FIG. 1.

At 302, a wireless session is registered for a wireless device, such asthe wireless device 102, by the wireless system 124. As used herein,“wireless session” refers to a period of time during which the wirelessdevice 102 accesses the supporting wireless system 124. A wirelesssession typically, but not necessarily, involves communication betweenthe wireless device 102 and one or more other entities (wireless orotherwise), access and use of the Internet or another network resource,access and use of one or more databases, etc. “Registration” refers toestablishing communication between the wireless device 102 and thewireless system 124 and, in one or more embodiments, initiating a recordwithin the database 126 of the wireless session. Such an initial recordcan include, for example, device and/or user identification, time anddate, one or more wireless signal protocol types, and the nature and/oridentity of resources to be accessed. Other initial information can alsobe included in the database 126 record.

At 304, the instantaneous geographic location and signal metrics for thepresent wireless session are determined by resources of the system 124.The geographic location of the wireless device 102 can be determined inany suitable way including, as non-limiting examples, global positionsystem (GPS) signals received by the wireless device 102 andcommunicated to the wireless system 124, triangulation on the wirelessdevice 102 by way of fixed wireless access points (e.g., cellular towers104, 106, 108, 110). Other methods of determining geographic location ofthe device 102, with some acceptable measure of precision, can also beused. Wireless signal metrics can include any quantified or classifiedwireless signal parameter of the wireless session including, forexample, overall signal strength, signal-to-noise ratio (SNR), failedversus successful wireless signal session status, etc. Other quantifiedand/or classified wireless signal parameters can also be defined aswireless signal metrics.

At 306, the signal integrity of the wireless session is evaluated usingone or more of the signal metrics determined at 304 above. If the signalintegrity is evaluated as inadequate in comparison to one or morepredetermined criteria—or if wireless communication with the wirelessdevice 102 has failed altogether—then the method 300 proceeds to 310 asdescribed below. If the signal integrity is determined to be acceptable,then the method 300 proceeds to 308 below.

At 308, the geographic location and signal metrics for the wirelesssession determined at 304 above are written to the database 126 asinitiated at 302 above. The method 300 then proceeds to 312 below.

At 310, the last known good geographic location and signal metrics forthe wireless session (as acquired on a previous iteration of steps 304,306, 308) are marked or tagged as such within the database 126. Themethod 300 then terminates.

At 312, it is determined if the present wireless session has been ended(terminated) by the user of the wireless device 102. Such determinationcan be based upon, for example, communication of an “END CALL” datasignal from the wireless device 102 to the system 124. The wirelesssession can be ended in other known ways, as well. If the wirelesssession has been ended, then such an indication is written to thedatabase 126 and the method 300 then terminates. If the wireless sessionhas not been ended by the user, the method 300 returns to 304 above.

The method 300 represents one suitable embodiment for acquiring datapertaining to wireless sessions and storing that data (typically, butnot necessarily) as discrete records (one record per wireless session)into a database, such as the database 126. In this way, a growingdeposit of information, representative of one or more wireless signalservice users, can be accumulated over time and analyzed for meaningfulcorrelations. As one example, correlations between poor signal strengthor “call dropping”, and a particular geographic location, can indicatelocalities where additional wireless system 124 resources are needed.Furthermore, such information can be used to advise users of wirelessdevices about areas prone to, or presently experiencing, wireless accesstrouble.

The method 300 of FIG. 3 is illustrative of numerous wireless sessiondata acquisition schemes in accordance with the present teachings. Othermethods including some or all of the steps 302, 304, 306, 308, 310, 312described above, or other steps, and/or other sequences of execution canalso be used and are within the scope of the present teachings. Themethod 300 can be implemented by way of any suitable construct such as,for example, one or more processors under software (e.g., media 130)control, one or more dedicated-purpose apparatus, etc. Furthermore,multiple instances of the method 300 can be performed simultaneously,each instance corresponding to a respective wireless session andassociated user.

Illustrative Syndrome Detection:

FIG. 4 is a flow diagram depicting an illustrative method 400 ofsyndrome detection in accordance with another embodiment. The method 400includes particular method steps and a particular order of execution.However, other embodiments can also be used that deviate in one or morerespects from the method 400 without departing from the scope of thepresent teachings. For purposes of illustration, the method 400 will bedescribed with reference to the operational scenario 100 of FIG. 1.

At 402, one or more resources of a wireless system, such as the wirelesssystem 124, are used to selectively define a relationship (or pattern)to be detected (i.e., sought) within a plurality of wireless signalsession data records. Such a relationship involves one or more wirelesssignal performance metrics within a geographic area. Non-limitingexamples of such relationships are described in further detailhereinafter. The relationship can be defined at the time of theexecution of method 400, or previously defined and retrieved from thedatabase 126 or another resource of the wireless system 124. In anycase, the relationship is selectively definable in accordance with user(e.g., system administrator) input and can involve correlation of anysuitable number of variables and/or parameters.

At 404, one or more resources of the wireless system 124 access thedatabase 126, which includes a plurality of wireless signal session datarecords. The database 126 can include, for example, data records writtenthereto in accordance with the method 300 of FIG. 3.

At 406, the plurality of wireless signal session data records areanalyzed to detect, or attempt to detect, the relationship defined at402 above. Such analysis can include, for example, regression analysis,probabilistic analysis, or any other suitable analytical, comparativeand/or correlative technique. In one example, all of the data recordsare analyzed in order to detect the relationship. In another example,the data records are first suitably filtered prior to further analysis.Such filtering can, for example, be performed on the basis of aparticular geographic area, wherein data records outside the geographicarea are not with the analytical set. Other suitable data preparationand handling techniques can also be used.

At 408, a report is generated in accordance with the detection (or lackthereof) at 406 above. The report is typically, but not necessarily,stored within the database 126 or another resource of the wirelesssystem 124 for immediate and/or later use. The report can, for example,be configured for access and use by other resources (e.g., the server128, etc.) of the wireless system 124. In one or more embodiments, thereport is configured (i.e., formatted) to be disseminated to a wirelessdevice, such as the wireless device 102. In this way, a user of thewireless system 124 can make use of the information within the report.

The methods 300 and 400, and any respective variations thereon, can beimplemented in any number of suitable ways. Non-limiting examples ofsuch implementations can include one or more processors under software(program code) control, one or more dedicated purpose apparatus,suitably configured resources within a wireless system (e.g., 124), etc.

FIG. 5 includes a listing 500 of illustrative predefined relationshipsthat can be sought and detected within a set of wireless signal sessiondata records. The listing 500 is non limiting in nature and variousother relationships can be selectively defined and used within the scopeof the present teachings.

The listing 500 includes a first relationship 502. The firstrelationship 502 is directed to detecting failed wireless signalsessions with a particular geographic region over a certain time period.According to exemplary embodiments, the first relationship 502 includesa region variable R1, a time period variable (or range) T1, and athreshold variable X1. The respective variables R1, T1 and X1 cancorrespond to any suitable scalars and units (i.e., vectors) such as,for example: R1=cellular service zone 44; T1=14:00-22:00 on 10 Jan.2006; and X1=40 failures. Other variables and units can also be definedand used. The first relationship 502, as depicted, is ambivalent to theparticular identity of the users/wireless devices involved in thedetection, but is concerned with a particular cellular service zone andtime/date period. Thus, the first relationship 502 is generally directedto detecting a “dropped calls” syndrome.

The listing 500 also includes a second relationship 504. According toexemplary embodiments, the second relationship 504 is directed todetecting the number of wireless devices, in excess of some threshold,that are continuously accessing a common wireless system resource over aperiod of time. Such a relationship, for example, can be directed todetecting stopped or “backed up” traffic along a particular section ofroadway with the service range of a wireless service resource (e.g.,operating scenario 200 of FIG. 2). The second relationship 504 mayinclude a resource variable RSI, a time period variable TI and athreshold variable X1. Illustrative scalars and units can be defined,for example, as: RSI=cellular tower 123XYZ; TI=11:00-11:05 continuouslyon 12 Jun. 2007; and X1=40 distinct wireless devices. Other variablesand units can also be defined and used. The second relationship 504, asdepicted, involves respective identities of the users/wireless devicesso as to detect continuous access over the time period underconsideration. Thus, the second relationship 504 is generally directedto detecting a syndrome involving a lack of propagation of a wirelesssignal sessions along a wireless service corridor.

The listing 500 also includes a third relationship 506. According toexemplary embodiments, the third relationship 506 is directed todetecting if the total number of wireless signal sessions within aparticular region, of a particular protocol type, that experienced asignal to-noise ratio over a certain value exceeds a defined count. Therelationship 506, for example, can be directed to detecting a syndromeinvolving inadequate service quality of a particular protocol typewithin a coverage area. In accordance with exemplary embodiments, thethird relationship 506 includes a protocol variable PI, a regionvariable RI, a signal-to-noise ratio variable SNRI, and a thresholdvariable X1. Illustrative scalars and units of the relationship 506 canbe defined, for example, as: PI=Wi-Fi®; region=hub 17; SNR=4.0 dB; andX1=90 wireless sessions total. Other suitable variables and units canalso be defined and used.

The listing 500 also includes a fourth relationship 508. According toexemplary embodiments, the fourth relationship 508 is directed todetecting the time period over which a particular wireless devicepropagates (i.e., is passed along) between first and second wirelessresources. Thus, the relationship 508 is directed to determining therate at which the particular wireless device is traversing through awireless signal coverage area. In accordance with exemplary embodiments,the fourth relationship 508 includes a wireless device identificationvariable ID1, a resource variable RS1 and a resource variable RS2, and atime period variable T1 that is to be detected or determined. Thus, therelationship 508 includes three input variable and one output variablewhen considered in the context of a function. Illustrative vectors ofthe relationship 508 can be defined, for example, as: IDI=serial number123456789; RSI=cellular tower 25; RS2=cellular tower 26; and T1 (to bedetermined)=seconds between respective, consecutive accesses. Othersuitable variables and units can also be defined and used.

The listing 500 of the relationships 502, 504, 506, 508 is illustrativeand non limiting. Any number of various, suitable relationships that canbe defined and detected (i.e., searched for) within a plurality ofwireless signal session data records within the scope of the presentteachings. Reports resulting from respective relationship detections canbe put to immediate or future use. Reports can be leveraged forimproving wireless signal services within a region or throughout asystem, for providing wireless service advisories to users, etc.

The methods 300 and 400, and any respective variations thereon, can beimplemented in any number of suitable ways. Non-limiting examples ofsuch implementations can include one or more processors under software(program code) control, one or more dedicated purpose apparatus,suitably configured resources within a wireless system (e.g., 124), etc.

CONCLUSION

Although the disclosure has been made in language specific to structuralfeatures and/or methodological acts, it is to be understood that thedisclosed concepts are not necessarily limited to the specific featuresor acts described. Rather, the specific features and acts are disclosedas exemplary implementations.

1. A method to monitor wireless system operation, the method comprising:processing, using a processor, a plurality of session records describingcharacteristics of wireless sessions in a coverage area of a wirelesssystem to determine a first time interval for a first wireless device topropagate from a first access point in the coverage area to a secondaccess point in the coverage area; determining, using the processor, acoverage area traversal rate for the first wireless device based on thefirst time interval, the coverage area traversal rate corresponding to arate at which the first wireless device is traversing the coverage area;and providing a wireless service advisory for the coverage area to asecond wireless device based on the coverage area traversal rate for thefirst wireless device.
 2. A method as defined in claim 1 whereinprocessing the plurality of session records includes performing at leastone of regression analysis or probabilistic analysis of at least some ofthe plurality of wireless signal session data records.
 3. A method asdefined in claim 1 wherein the plurality of session records areassociated with a respective plurality of wireless devices.
 4. A methodas defined in claim 1 further comprising: retrieving the plurality ofsession records from a database; and filtering the plurality of sessionrecords based on a geographic location of the coverage area.
 5. A methodas defined in claim 1 wherein a first session record for a firstwireless session associated with the first wireless device includes: adevice identifier for the first wireless device; identificationinformation for each access point accessed by the wireless device duringfirst wireless session; and time information.
 6. A method as defined inclaim 5 wherein processing the plurality of session records includescomparing corresponding fields in the plurality of session records to aspecified device identifier variable identifying the first wirelessdevice, a first specified resource variable identifying the first accesspoint and a second specified resource variable identifying the secondaccess point.
 7. A tangible machine readable storage medium storingmachine readable instructions which, when executed, cause a machine toperform operations comprising: processing a plurality of session recordsdescribing characteristics of wireless sessions in a coverage area of awireless system to determine a first time interval for a first wirelessdevice to propagate from a first access point in the coverage area to asecond access point in the coverage area; determining a coverage areatraversal rate for the first wireless device based on the first timeinterval, the coverage area traversal rate corresponding to a rate atwhich the first wireless device is traversing the coverage area; andproviding a wireless service advisory for the coverage area to a secondwireless device based on the coverage area traversal rate for the firstwireless device.
 8. A storage medium as defined in claim 7 whereinprocessing the plurality of session records includes performing at leastone of regression analysis or probabilistic analysis of at least some ofthe plurality of wireless signal session data records.
 9. A storagemedium as defined in claim 7 wherein the plurality of session recordsare associated with a respective plurality of wireless devices.
 10. Astorage medium as defined in claim 7 wherein the operations furthercomprise: retrieving the plurality of session records from a database;and filtering the plurality of session records based on a geographiclocation of the coverage area.
 11. A storage medium as defined in claim7 wherein a first session record for a first wireless session associatedwith the first wireless device includes: a device identifier for thefirst wireless device; identification information for each access pointaccessed by the wireless device during first wireless session; and timeinformation.
 12. A storage medium as defined in claim 11 whereinprocessing the plurality of session records includes comparingcorresponding fields in the plurality of session records to a specifieddevice identifier variable identifying the first wireless device, afirst specified resource variable identifying the first access point anda second specified resource variable identifying the second accesspoint.
 13. An apparatus to monitor wireless system operation, theapparatus comprising: a memory to store machine readable instructions;and a processor to execute the machine readable instructions to causethe processor to perform operations comprising: processing a pluralityof session records describing characteristics of wireless sessions in acoverage area of a wireless system to determine a first time intervalfor a first wireless device to propagate from a first access point inthe coverage area to a second access point in the coverage area;determining a coverage area traversal rate for the first wireless devicebased on the first time interval, the coverage area traversal ratecorresponding to a rate at which the first wireless device is traversingthe coverage area; and providing a wireless service advisory for thecoverage area to a second wireless device based on the coverage areatraversal rate for the first wireless device.
 14. An apparatus asdefined in claim 13 wherein processing the plurality of session recordsincludes performing at least one of regression analysis or probabilisticanalysis of at least some of the plurality of wireless signal sessiondata records.
 15. An apparatus as defined in claim 13 wherein theplurality of session records are associated with a respective pluralityof wireless devices.
 16. An apparatus as defined in claim 13 wherein theoperations further comprise: retrieving the plurality of session recordsfrom a database; and filtering the plurality of session records based ona geographic location of the coverage area.
 17. An apparatus as definedin claim 13 wherein a first session record for a first wireless sessionassociated with the first wireless device includes: a device identifierfor the first wireless device; identification information for eachaccess point accessed by the wireless device during first wirelesssession; and time information.
 18. An apparatus as defined in claim 17wherein processing the plurality of session records includes comparingcorresponding fields in the plurality of session records to a specifieddevice identifier variable identifying the first wireless device, afirst specified resource variable identifying the first access point anda second specified resource variable identifying the second accesspoint.